Scenes from an Analytics Journey

Scenes from an Analytics Journey

By Gary Angel

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April 29, 2019

Analytics Journey

This past week or so I posted a long series of tweets based on my upcoming presentation at the Marketing Analytics Summit in Las Vegas. #MAS19 bit.ly/MAS19LV

 

The presentation is structured as an analytics journey – from building reports to democratize data, tackling real analysis and struggling with data quality, and even finding that for all your good work you don’t have a seat at the table. Along the way, it highlights the things I’ve learned about how to move forward and do better over a couple decades of tackling these problems and living this particular journey.

 

But absorbing it piecemeal on Twitter is a bit of work. So I’ve collected them all here in one nice simple (slightly expanded – bugger Twitter’s character limits) flow:

 

Scene 1

Entrance: You start by trying to deliver data to your users. Reporting looks like such a big, easy win.

Exit: You realize reporting is mostly a waste of time. Most reports are never viewed. Most reports that are viewed are misunderstood. And most reports that are viewed and understood don’t make any difference…

 

Scene 2

Entrance: So you focus on doing real analysis to answer key business questions. And, of course, the first thing you discover when you start doing analytics?

Exit: Is that your data sucks.

 

Scene 3

Entrance: After a grueling parallel effort of analytics and data governance, your data is finally in shape and you start delivering real analysis.

Exit: When you’ll realize the hard part of analytics isn’t crunching numbers.

 

Scene 4

Entrance: Because organizational culture inevitably slows or stops analytics-driven change.

Exit: Building culture is insanely hard. But one of the really clever ways to do it? Learning that seeding questions is better than giving answers.

 

Scene 5

Entrance: But no matter how much success you’ve had, blind-spots remain in the enterprise.

Exit: Forecasting is probably one of them. It shouldn’t be. Forecasting is one of the most analytic things the enterprise does. Treat it with the respect it deserves.

 

Scene 6

Entrance: The biggest complaint from mature, successful analtyics practices? We do good analytics but we’re not in the room where it happens.

Exit: This is a you problem. You’re analytics is all tactical not strategic. VoC is critical to making analytics more strategic.

 

Scene 7

Entrance: So you focus on VoC to be more strategic.

Exit: And you realize your existing VoC is boring, too long and ill-focused. Current enterprise VoC efforts just suck.

 

Scene 8

Entrance: Focusing VoC away from scoreboard metrics (looking at you NPS) and toward customer drivers of decision will inevitably create loads of behavioral questions for which you lack data.

Exit: Which should drive a broader focus on experimentation.

 

Scene 9

Entrance: Aggressive efforts to build out a testing program often exposes deep flaws in the customer journey model – because you don’t know what to test or why it’s important.

Exit: Time to re-think how you build and maintain journey maps. This should NOT be a one-off exercise.

 

Scene 10

Entrance: Success in analytics brings its own challenges – which is why real journeys never have an endpoint.

Exit: Growth and success create silos. Silos limit opportunity and build organizational friction. Removing growth-based silos is a never-ending battle in the enterprise.

 

The road goes ever on an on. But every presentation has a time-limit. So I’ve ended this particular analytics journey here. I hope you’ll join me in Las Vegas at the Summit to hear the real thing! bit.ly/MAS19LV

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